@article{Ercal1994Neural,
  title={Neural network diagnosis of malignant melanoma from color images},
  author={Ercal, F. ,. and Chawla, A. ,. and Stoecker, W V, and Lee, H C, and Moss, R H,},
  journal={IEEE Transactions on Biomedical Engineering},
  volume={41},
  number={9},
  pages={837-845},
  year={1994},
}

@article{Mishra2016An,
  title={An Overview of Melanoma Detection in Dermoscopy Images Using Image Processing and Machine Learning},
  author={Mishra, Nabin K and Celebi, M Emre},
  year={2016},
}

@article{Codella2019Skin,
  title={Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)},
  author={Codella, Noel and Rotemberg, Veronica and Tschandl, Philipp and Celebi, M. Emre and Halpern, Allan},
  year={2019},
}

@article{Zortea2014Performance,
  title={Performance of a dermoscopy-based computer vision system for the diagnosis of pigmented skin lesions compared with visual evaluation by experienced dermatologists},
  author={Zortea, Maciel and Schopf, Thomas R. and Thon, Kevin and Geilhufe, Marc and Hindberg, Kristian and Kirchesch, Herbert and Møllersen, Kajsa and Schulz, Jörn and Skrøvseth, Stein Olav and Godtliebsen, Fred},
  journal={Artificial Intelligence in Medicine},
  volume={60},
  number={1},
  pages={13-26},
  year={2014},
}

@article{He2015Deep,
  title={Deep Residual Learning for Image Recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  year={2015},
}

@article{Fei2017Residual,
  title={Residual Attention Network for Image Classification},
  author={Fei, Wang and Jiang, Mengqing and Chen, Qian and Yang, Shuo and Cheng, Li and Zhang, Honggang and Wang, Xiaogang and Tang, Xiaoou},
  year={2017},
}

@article{Jie2017Squeeze,
  title={Squeeze-and-Excitation Networks},
  author={Jie, Hu and Li, Shen and Gang, Sun and Jie, Hu and Li, Shen and Gang, Sun},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume={PP},
  number={99},
  pages={1-1},
  year={2017},
}

@article{Bottou2010Large,
  title={Large-Scale Machine Learning with Stochastic Gradient Descent},
  author={Bottou, Léon},
  year={2010},
}

@article{Ruder2017An,
  title={An overview of gradient descent optimization algorithms},
  author={Ruder, Sebastian},
  year={2017},
}

@article{Andrychowicz2016Learning,
  title={Learning to learn by gradient descent by gradient descent},
  author={Andrychowicz, Marcin and Denil, Misha and Gomez, Sergio and Hoffman, Matthew W. and Pfau, David and Schaul, Tom and Freitas, Nando De},
  year={2016},
}

@article{Barakat2018Convergence,
  title={Convergence and Dynamical Behavior of the ADAM Algorithm for Non Convex Stochastic Optimization},
  author={Barakat, Anas and Bianchi, Pascal},
  year={2018},
}

@article{Zhang2018ADAM,
  title={ADAM-ADMM: A Unified, Systematic Framework of Structured Weight Pruning for DNNs},
  author={Zhang, Tianyun and Zhang, Kaiqi and Ye, Shaokai and Li, Jiayu and Wang, Yanzhi},
  year={2018},
}

@article{Jain2018A,
  title={A Fast Adaptive Algorithm for Computing Whole-Genome Homology Maps},
  author={Jain, Chirag and Koren, Sergey and Dilthey, Alexander and Phillippy, Adam M. and Aluru, Srinivas},
  journal={Bioinformatics},
  volume={34},
  number={17},
  pages={i748-i756},
  year={2018},
}

@article{Nguyen2018When,
  title={When Does Stochastic Gradient Algorithm Work Well?},
  author={Nguyen, Lam M. and Nguyen, Nam H. and Phan, Dzung T. and Kalagnanam, Jayant R. and Scheinberg, Katya},
  year={2018},
}

@article{Bianco2016On,
  title={On the use of deep learning for blind image quality assessment},
  author={Bianco, Simone and Celona, Luigi and Napoletano, Paolo and Schettini, Raimondo},
  journal={Signal Image & Video Processing},
  number={3},
  pages={1-8},
  year={2016},
}

@article{hong2017automatic,
  title={Automatic Recognition of Coal and Gangue based on Convolution Neural Network},
  author={Hong, Huichao and Zheng, Lixin and Zhu, Jianqing and Pan, Shuwan and Zhou, Kaiting},
  journal={arXiv preprint arXiv:1712.00720},
  year={2017}
}

@article{pu2019image,
  title={Image Recognition of Coal and Coal Gangue Using a Convolutional Neural Network and Transfer Learning},
  author={Pu, Yuanyuan and Apel, Derek B and Szmigiel, Alicja and Chen, Jie},
  journal={Energies},
  volume={12},
  number={9},
  pages={1735},
  year={2019},
  publisher={Multidisciplinary Digital Publishing Institute}
}

@article{hou2019identification,
  title={Identification of coal and gangue by feed-forward neural network based on data analysis},
  author={Hou, Wei},
  journal={International Journal of Coal Preparation and Utilization},
  volume={39},
  number={1},
  pages={33--43},
  year={2019},
  publisher={Taylor \& Francis}
}

@inproceedings{su2018research,
  title={Research on Coal Gangue Identification by Using Convolutional Neural Network},
  author={Su, Lingling and Cao, Xiangang and Ma, Hongwei and Li, Ying},
  booktitle={2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)},
  pages={810--814},
  year={2018},
  organization={IEEE}
}

@article{cao2019,
  title={基于迁移学习的GoogLenet煤矸石图像识别},
  author={曹现刚},
  journal={软件导刊},
  pages={1--4},
  year={2019}
}

@article{zz,
  author = {朱志华},
  title = {https://github.com/zhuzhu18/Unet-pytorch}
}

@inproceedings{ronnebergerconvolutional,
  title={Convolutional networks for biomedical image segmentation},
  author={Ronneberger, O and Fischer, P and Brox, TU-net},
  booktitle={Paper presented at: International Conference on Medical Image Computing and Computer-Assisted Intervention2015}
}